Sep 23–26, 2019
Matthew Horton

Matthew Horton
Senior Director, Data Science, Major League Baseball

Matt Horton is the senior director of data science at Major League Baseball (MLB). In his 11+ years at MLB, Matt has developed numerous projects including predicting ticket buyers’ future purchasing behavior to aid teams in prioritizing their marketing efforts and building a framework for predicting and preventing subscriber churn for MLB’s game-streaming service, MLB.TV. Matt’s team is focused on quantifying fans’ relationships with their favorite teams, modeling trends in both team and league-wide attendance, and estimating fans’ future engagement with MLB. Previously, Matt was at Rosetta and Accenture. He has a BS in statistics from the University of Tennessee and a master’s in applied statistics from Cornell University.
In addition to him being a huge baseball fan, Matt is also an avid fan of sports in general, rooting for teams from his home state of Tennessee, including the Volunteers, Titans, Predators, and Grizzlies.

Sessions

5:25pm6:05pm Wednesday, September 25, 2019
Location: 1A 08/10
Secondary topics:  Media and Advertising
Aaron Owen (Major League Baseball), Matthew Horton (Major League Baseball), Josh Hamilton (Major League Baseball)
Using SAS, Python, and AWS SageMaker, Major League Baseball's (MLB's) data science team outlines how it predicts ticket purchasers’ likelihood to purchase again, evaluates prospective season schedules, estimates customer lifetime value, optimizes promotion schedules, quantifies the strength of fan avidity, and monitors the health of monthly subscriptions to its game-streaming service. Read more.

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